1. Field of the Invention
The present invention relates to an object pose normalization apparatus and method, and a method of recognizing an object, and more particularly, to a method of normalizing a non-frontal facial image to a frontal facial image. The method of normalizing a pose of an object can be used in multi-view face recognition systems, video morphing systems, monitoring systems, and digital photo retrieval systems.
2. Description of the Related Art
V. Blanz and T. Vetter have disclosed a method of rendering a facial image having a variety of poses in a 3 dimensional (3D) space in “Face Recognition based on Fitting a 3D Morphable Model (2003)”. The 3D morphable model is based on a method of synthesizing a new facial image by using a variety of already known 3D shapes and texture information. FIG. 1 is a reference diagram illustrating examples of synthesizing facial images 10. However, the 3D morphable model has a problem of computational complexity due to calculation of a large number of optimized parameters, and has a disadvantage in terms of initialization of feature points and automatic localization.
Among conventional 2D approaches, there is a method of synthesizing a facial image in which 2D object feature points are detected by using active appearance models (AAMs) or active shape models (ASMs), and by using the detected object feature points, a facial image is synthesized. The AAMs or ASMs use principle component analysis (PCA) or the like in order to model a statistical facial shape and a gray scale. The 2D approaches are methods of transforming texture information of a face to a given shape by Affine-transforming each of triangles formed by the detected facial feature points. An example of synthesizing a facial image by using the ASM is illustrated in the images 20 of FIG. 1. As can be confirmed from FIG. 1, the 2D approaches, such as the ASM, have a problem in that it is difficult to restore a part in which self occlusion occurs. Also, only with the Affine transformation, is a non-rigid deformation unable to be compensated for, and the authentication ratio of face recognition is limited because a gray scale, a shape, and the position of a feature point vary with respect to changes in a pose.
Although a variety of techniques for synthesizing an image have been disclosed as described above, a technology of normalizing a pose of an object by using a 2D image processing technology and utilizing the normalized pose in facial recognition has not yet been disclosed.